# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


_import_structure = {
    "configuration_perceiver": ["PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PerceiverConfig", "PerceiverOnnxConfig"],
    "tokenization_perceiver": ["PerceiverTokenizer"],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["feature_extraction_perceiver"] = ["PerceiverFeatureExtractor"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_perceiver"] = [
        "PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "PerceiverForImageClassificationConvProcessing",
        "PerceiverForImageClassificationFourier",
        "PerceiverForImageClassificationLearned",
        "PerceiverForMaskedLM",
        "PerceiverForMultimodalAutoencoding",
        "PerceiverForOpticalFlow",
        "PerceiverForSequenceClassification",
        "PerceiverLayer",
        "PerceiverModel",
        "PerceiverPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverOnnxConfig
    from .tokenization_perceiver import PerceiverTokenizer

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_perceiver import PerceiverFeatureExtractor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_perceiver import (
            PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST,
            PerceiverForImageClassificationConvProcessing,
            PerceiverForImageClassificationFourier,
            PerceiverForImageClassificationLearned,
            PerceiverForMaskedLM,
            PerceiverForMultimodalAutoencoding,
            PerceiverForOpticalFlow,
            PerceiverForSequenceClassification,
            PerceiverLayer,
            PerceiverModel,
            PerceiverPreTrainedModel,
        )

else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
